Abstract
The neuropathological hallmark of the C9orf72 intronic hexanucleotide expansion in frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) is the presence of small ...ubiquitin/p62-positive and transactive response DNA binding protein 43 kDa (TDP-43)-negative cytoplasmic inclusions in several brain areas. The identification of this histopathological signature is highly predictive of an underlying mutation. In this study, we screened 1800 cases of the Barcelona IDIBAPS Brain Bank, independently of the clinical and final neuropathological diagnosis of the brain donor, for the presence of ubiquitin/p62-positive inclusions in the cerebellum (UPPI). Positive cases were also stained for dipeptide repeats. We identified a total of 21 donors with UPPI and in all of them the C9orf72 hexanucleotide expansion was genetically confirmed. Most donors had an FTLD or to a lesser extent ALS clinico-pathological phenotype. However, 3 cases had been previously classified as having clinically and neuropathologically Lewy body disease. Other co-existing pathologies, especially of the PART-type, were also frequently encountered. This study highlights the importance of the evaluation of ubiquitin/p62-positive cytoplasmic inclusions in all neurodegenerative diseases as a good screening method for the detection of C9orf72 expansion mutation, since this mutation is not rare and can overlap with other neurodegenerative entities.
Background
Early‐onset Alzheimer’s Disease presentations (EOAD, under 65) frequently present with atypical phenotypes and a more aggressive disease course with a higher burden of neuropsychiatric ...symptoms than late‐onset AD (LOAD). Current treatments for sleep and behavioral disturbances are still non‐specific, causing side effects (e.g., sedation, falls). Identifying the underlying changes driving behavioral differences between EOAD and LOAD is crucial to developing tailored treatment avenues. The noradrenergic locus coeruleus (LC), one of the first sites of tau deposition in AD, has been implicated in sleep‐wake patterns and mood regulation. We aim to test the hypothesis that the LC is more affected in EOAD than LOAD by comparing LC volume (neuromelanin‐sensitive MRI) and sleep‐behavioral symptoms in biomarker‐confirmed EOAD and LOAD cohorts.
Method
Fifty‐four subjects with AD biomarker‐based diagnosis (20 EOAD, 34 LOAD) were recruited at the Hospital Clínic de Barcelona. All participants and informants completed the Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), and Neuropsychiatric Inventory (NPI) questionnaires to assess the severity of sleep‐wake alterations and neuropsychiatric symptoms. In addition, they underwent a 3T turbospin‐echo MRI to measure LC volume. We compared mean values of LC volume, ESS, PSQI, and NPI between EOAD and LOAD. Furthermore, linear regression models controlling by cognitive status (MMSE) were performed.
Result
EOAD and LOAD had similar cognition (MMSE 21.3±5 vs. 22.6±4, respectively), functional status (CDR 0.92±0.1 vs. 0.68±0.1), and prevalence of amnestic phenotype (57 vs. 70%). EOAD compared to LOAD, trended towards higher scores for ESS (7.4±1 vs. 5.1±1, respectively), PSQI (7.3±2 vs. 5.6±1), NPI (21.6±8 vs. 14.6±8), and caregiver distress (9.4±3 vs. 4.7±3). LC volume was lower in EOAD according to preliminary MRI data n=18, 9 EOAD (21.8±3 mm3), 9 LOAD (29.5±3 mm3). Linear regression models showed that MMSE did not influence the EOAD/LOAD effect on LC volume (coef. 7.7, p=0.032).
Conclusion
The current preliminary study suggests that LC degeneration is greater in EOAD than LOAD. This difference may explain the EOAD‐associated worse sleep‐wake dysfunction and neuropsychiatric symptoms. Deep phenotyping/comparison of EOAD and LOAD can inform tailored treatment strategies for these behavioral symptoms.
Background
Early‐onset Alzheimer’s disease (EOAD, onset before 65 years), is the most common early‐onset neurodegenerative dementia. However, it still represents a diagnostic challenge especially ...when compared with late‐onset Alzheimer’s disease (LOAD). Our aim was to describe and compare the neuropsychological presentation at diagnosis and its progression in patients with EOAD and LOAD.
Methods
One‐hundred ninety‐five participants were included and classified accordingly to their CSF AD biomarker profile and clinical status: 46 young controls (Y‐CTR) aged below 65 years (age=57.4±4.7; MMSE=28.7±1.6), 23 old controls (O‐CTR) aged 65 or above (age=69.7±3.7; MMSE=28.0±1.4), 89 EOAD (age=59.8±4.2; MMSE=22.6±3.9) and 37 LOAD (age=74.5±4.8; MMSE=24.3±3.1). All subjects underwent clinical and neuropsychological assessment, APOE genotyping and lumbar puncture at baseline. Clinical and neuropsychological follow‐up was performed annually over 2 years.
Results
No differences were found in terms of gender or years of education among the study groups. APOE4 was more frequent in EOAD and LOAD groups than controls (p<0.01). As expected, the control groups presented higher CSF Aβ42 and lower CSF tau and p‐tau levels than AD groups (Table 1). Baseline neuropsychological assessment (Figure 1) revealed differences between EOAD and LOAD in global cognitive function (p<0.05), ideomotor (p<0.05) and constructional (p<0.01) praxis, visuoperceptive (p<0.05) and visuospatial (p<0.01) function and working memory (p<0.05). When comparing controls and AD groups, EOAD performed significantly worse than Y‐CTR in all cognitive domains while LOAD showed differences with O‐CTR in memory, language and executive function but obtained a similar performance in ideomotor and constructional praxis, visuospatial function, attention and working memory. Longitudinally (Figure 2), no differences between EOAD and LOAD were observed on memory or language domains but EOAD showed higher decline in global cognitive function (p<0.05), ideomotor (p<0.05) and constructional (p<0.01) praxis, visuoperceptive (p<0.05) and visuospatial (p<0.01) function, attention (p<0.05) and working memory (p<0.05).
Conclusions
Early‐ and late‐onset AD present distinct neuropsychological profiles at diagnosis with EOAD displaying higher difficulties in non‐memory domains and a more aggressive course. The present data may help on enhancing EOAD diagnosis and therefore on ensuring an earlier intervention in this population.
Abstract
Background
ABCA7
gene (ATP‐binding cassette transporter A7) loss‐of‐function mutations are related to increased risk of suffering Alzheimer’s disease (AD). On the other hand, mutations in
...GRN
(Progranulin) gene are causative of frontotemporal dementia (FTD).
Methods
The proband was a patient diagnosed from semantic variant of primary progressive aphasia. Age at onset was at 50 years‐old, presenting progressive cognitive decline with an important language loss. The MRI showed a left temporal atrophy. AD CSF biomarkers were normal and no familial history of dementia was reported. Next generation sequencing was performed with Illumina NextSeq500. Single nucleotide variants were detected using GATK and copy number variants using ExomeDepth algorithm. Sanger sequencing was performed for
GRN
variant confirmation and MLPA technique for
ABCA7
deletion validation.
C9orf72
repeat expansion was studied with a repeat primed PCR and fragment analysis. Biological samples from his mother and a brother were obtained. Commercial ELISA kit was used to measure serum PGRN levels (Adipogen).
Results
Patient showed an
ABCA7
partial deletion (exons 17‐47) plus 4 contiguous genes, of a total of 105 kb in size (hg19 chr19:g.1048865_1154298). Deletion was confirmed in the proband and discarded in the proband’s mother and brother by MLPA. Patient and his mother (asymptomatic at 81 yo) were also carriers of a reported
GRN
variant, p.(Asp33Glu; rs63750742). Progranulin serum levels were normal in the patient and his family members.
C9orf72
screening was negative.
Conclusions
The patient harbored two genetic alterations in genes related to dementia risk, although it is unlikely that any of them alone could be responsible of the FTD phenotype.
ABCA7
deletion should be
de novo
or father inherited.
ABCA7
protein truncating variant at exon 14 (p.Arg578fs), which has a similar protein consequence, is relatively frequent in control population, although has showed a 1.8‐fold enrichment in AD patients. Moreover,
GRN
variant does not seem to be pathogenic or low penetrance because proband’s mother is unaffected and serum progranulin levels are normal. In conclusion, these variants
per se
are likely not sufficient to cause the disease, but rather risk variants of intermediate to high penetrance along with other factors.
Background
Early‐onset dementia (EOD; <65 years) raises both diagnostic and social/health care challenges. Services for dementia are often designed for the elderly and might have difficulties ...supplying EOD needs. Clinical and epidemiological data are needed for care planning.
Method
We aim to describe the demographic and the clinical characteristics of all the new referrals to our EOD clinic during the last 4 years (2016‐2019). Clinical charts were reviewed retrospectively. Both, sporadic and genetic cases were included in the analysis. We evaluate the type of symptoms, type and frequency of ancillary tests requested and final diagnosis.
Results
We evaluated 477 new early‐onset patients mean age at consultation (MAC) 54.6 years (SD=±9.6), 56% female during this period. The aim of the first visit was genetic counseling in 17.8% MAC 48.3(±13.3), 55.3% female and evaluation of sporadic cases in 82.2% MAC 56(±8), 56.1% female Figures 1 & 2. Among sporadic cases, memory complains were the main symptom (67.1%), followed by behavioral (13%) and language disturbance (11.2%). Complete neuropsychological evaluation was performed in 61.2%, CSF biomarkers in 30.9%, PET‐FDG in 22.4%, PET‐amyloid in 12.5% and genetic testing in 10.5%. Subjective Cognitive Decline (SCD) was diagnosed in 51.8% of these sporadic cases MAC 54.2(±8), 63.5% female, Mean MMSE 27(±4), while an abnormal cognition was found in the 48.2% MAC 58(±7.5), 48.1% female, Mean MMSE 23(±6). Regarding EOD causes, 54% was due to neurodegenerative dementias MAC 60(±5.5), 47.1% females, MMSE 22(±6) and 46% to non‐neurodegenerative MAC 55.5(±8.8), 49.4% female, Mean MMSE 25(±5). EOD mean time to diagnosis was 3.1 years (±3.75) with no differences between groups (p=0,207). In neurodegenerative dementias, AD constitutes 51% MAC 61.6(±4), 51.9% female, Mean MMSE 20(±6) and Frontotemporal lobular degeneration (FTLD) 34.3% MAC 58.5(±5.3), 45,7% female, Mean MMSE 24(±5).
Conclusion
SCD is a frequent diagnosis among new referrals to EOD clinics. AD is the most frequent neurodegenerative EOD, followed by FTLD. Non‐neurodegenerative causes of EOD are frequent and heterogeneous. Long delay until diagnosis suggests that new care policies are needed to identify EOD in early stages.
Abstract
Background
Early‐onset dementia (EOD; <65 years) raises both diagnostic and social/health care challenges. Services for dementia are often designed for the elderly and might have ...difficulties supplying EOD needs. Clinical and epidemiological data are needed for care planning.
Method
We aim to describe the demographic and the clinical characteristics of all the new referrals to our EOD clinic during the last 4 years (2016‐2019). Clinical charts were reviewed retrospectively. Both, sporadic and genetic cases were included in the analysis. We evaluate the type of symptoms, type and frequency of ancillary tests requested and final diagnosis.
Results
We evaluated 477 new early‐onset patients mean age at consultation (MAC) 54.6 years (SD=±9.6), 56% female during this period. The aim of the first visit was genetic counseling in 17.8% MAC 48.3(±13.3), 55.3% female and evaluation of sporadic cases in 82.2% MAC 56(±8), 56.1% female Figures 1 & 2. Among sporadic cases, memory complains were the main symptom (67.1%), followed by behavioral (13%) and language disturbance (11.2%). Complete neuropsychological evaluation was performed in 61.2%, CSF biomarkers in 30.9%, PET‐FDG in 22.4%, PET‐amyloid in 12.5% and genetic testing in 10.5%. Subjective Cognitive Decline (SCD) was diagnosed in 51.8% of these sporadic cases MAC 54.2(±8), 63.5% female, Mean MMSE 27(±4), while an abnormal cognition was found in the 48.2% MAC 58(±7.5), 48.1% female, Mean MMSE 23(±6). Regarding EOD causes, 54% was due to neurodegenerative dementias MAC 60(±5.5), 47.1% females, MMSE 22(±6) and 46% to non‐neurodegenerative MAC 55.5(±8.8), 49.4% female, Mean MMSE 25(±5). EOD mean time to diagnosis was 3.1 years (±3.75) with no differences between groups (p=0,207). In neurodegenerative dementias, AD constitutes 51% MAC 61.6(±4), 51.9% female, Mean MMSE 20(±6) and Frontotemporal lobular degeneration (FTLD) 34.3% MAC 58.5(±5.3), 45,7% female, Mean MMSE 24(±5).
Conclusion
SCD is a frequent diagnosis among new referrals to EOD clinics. AD is the most frequent neurodegenerative EOD, followed by FTLD. Non‐neurodegenerative causes of EOD are frequent and heterogeneous. Long delay until diagnosis suggests that new care policies are needed to identify EOD in early stages.
Abstract
Background
Early‐onset Alzheimer’s disease (EOAD, onset before 65 years), is the most common early‐onset neurodegenerative dementia. However, it still represents a diagnostic challenge ...especially when compared with late‐onset Alzheimer’s disease (LOAD). Our aim was to describe and compare the neuropsychological presentation at diagnosis and its progression in patients with EOAD and LOAD.
Methods
One‐hundred ninety‐five participants were included and classified accordingly to their CSF AD biomarker profile and clinical status: 46 young controls (Y‐CTR) aged below 65 years (age=57.4±4.7; MMSE=28.7±1.6), 23 old controls (O‐CTR) aged 65 or above (age=69.7±3.7; MMSE=28.0±1.4), 89 EOAD (age=59.8±4.2; MMSE=22.6±3.9) and 37 LOAD (age=74.5±4.8; MMSE=24.3±3.1). All subjects underwent clinical and neuropsychological assessment, APOE genotyping and lumbar puncture at baseline. Clinical and neuropsychological follow‐up was performed annually over 2 years.
Results
No differences were found in terms of gender or years of education among the study groups. APOE4 was more frequent in EOAD and LOAD groups than controls (p<0.01). As expected, the control groups presented higher CSF Aβ
42
and lower CSF tau and p‐tau levels than AD groups (Table 1). Baseline neuropsychological assessment (Figure 1) revealed differences between EOAD and LOAD in global cognitive function (p<0.05), ideomotor (p<0.05) and constructional (p<0.01) praxis, visuoperceptive (p<0.05) and visuospatial (p<0.01) function and working memory (p<0.05). When comparing controls and AD groups, EOAD performed significantly worse than Y‐CTR in all cognitive domains while LOAD showed differences with O‐CTR in memory, language and executive function but obtained a similar performance in ideomotor and constructional praxis, visuospatial function, attention and working memory. Longitudinally (Figure 2), no differences between EOAD and LOAD were observed on memory or language domains but EOAD showed higher decline in global cognitive function (p<0.05), ideomotor (p<0.05) and constructional (p<0.01) praxis, visuoperceptive (p<0.05) and visuospatial (p<0.01) function, attention (p<0.05) and working memory (p<0.05).
Conclusions
Early‐ and late‐onset AD present distinct neuropsychological profiles at diagnosis with EOAD displaying higher difficulties in non‐memory domains and a more aggressive course. The present data may help on enhancing EOAD diagnosis and therefore on ensuring an earlier intervention in this population.
Background
ABCA7 gene (ATP‐binding cassette transporter A7) loss‐of‐function mutations are related to increased risk of suffering Alzheimer’s disease (AD). On the other hand, mutations in GRN ...(Progranulin) gene are causative of frontotemporal dementia (FTD).
Methods
The proband was a patient diagnosed from semantic variant of primary progressive aphasia. Age at onset was at 50 years‐old, presenting progressive cognitive decline with an important language loss. The MRI showed a left temporal atrophy. AD CSF biomarkers were normal and no familial history of dementia was reported. Next generation sequencing was performed with Illumina NextSeq500. Single nucleotide variants were detected using GATK and copy number variants using ExomeDepth algorithm. Sanger sequencing was performed for GRN variant confirmation and MLPA technique for ABCA7 deletion validation. C9orf72 repeat expansion was studied with a repeat primed PCR and fragment analysis. Biological samples from his mother and a brother were obtained. Commercial ELISA kit was used to measure serum PGRN levels (Adipogen).
Results
Patient showed an ABCA7 partial deletion (exons 17‐47) plus 4 contiguous genes, of a total of 105 kb in size (hg19 chr19:g.1048865_1154298). Deletion was confirmed in the proband and discarded in the proband’s mother and brother by MLPA. Patient and his mother (asymptomatic at 81 yo) were also carriers of a reported GRN variant, p.(Asp33Glu; rs63750742). Progranulin serum levels were normal in the patient and his family members. C9orf72 screening was negative.
Conclusions
The patient harbored two genetic alterations in genes related to dementia risk, although it is unlikely that any of them alone could be responsible of the FTD phenotype. ABCA7 deletion should be de novo or father inherited. ABCA7 protein truncating variant at exon 14 (p.Arg578fs), which has a similar protein consequence, is relatively frequent in control population, although has showed a 1.8‐fold enrichment in AD patients. Moreover, GRN variant does not seem to be pathogenic or low penetrance because proband’s mother is unaffected and serum progranulin levels are normal. In conclusion, these variants per se are likely not sufficient to cause the disease, but rather risk variants of intermediate to high penetrance along with other factors.
Background
The amyloid deposition (A) in the 2018 ATN classification of Alzheimer disease can be assessed by CSF Aβ 1‐42 or amyloid PET. Although the agreement between them is high, it is not exact.
...Method
We selected patients from the Alzheimer’s disease and other cognitive disorders Unit at Hospital Clínic of Barcelona with available amyloid PET and lumbar puncture, with a maximum difference of time of one and a half year between them. We used F18 Florbetapir (n=27), F18 Florbetaben (n=7), F18 Flutemetamol (n=16) or 11C‐PIB (n=2) as tracers for amyloid PET. CSF Aβ 1‐42, total tau (tTau) and phosphorylated tau (pTau) were measured using INNOTEST® Fujirebio until June 2019 and using LUMIPULSE® Fujirebio after June 2019. We analyzed the agreement between amyloid PET and CSF biomarkers.
Result
We included 52 patients. They had been diagnosed of Alzheimer disease (n=32), frontotemporal dementia (n=11), Lewy body disease (n=2) and psychiatric disorders (n=7) (Table 1).
There was a perfect agreement between CSF biomarkers and amyloid PET when CSF biomarkers were all normal or all altered (Figure 1): All patients with CSF A+T+N+ (n=19) had a positive amyloid PET and all patients with CSF A‐T‐N‐ (n=7) had a negative amyloid PET. Agreement decreased with other CSF results. Only 11/19 patients with CSF A+T‐N‐ had a positive amyloid PET. 31/32 (97%) patients with positive amyloid PET had low Aβ 1‐42 levels (A+) but only 11/20 (55%) patients with negative amyloid PET had normal Aβ 1‐42 levels (A‐).
Conclusion
CSF biomarkers and amyloid PET showed a perfect agreement when CSF biomarkers were all normal or all altered. For other CSF ATN results, agreement with amyloid PET was much lower.
Abstract
Background
Changes in functional connectivity (FC) networks have been extensively reported in late onset Alzheimer’s Disease (AD), being the default mode network (DMN) the key system to be ...affected. However, it remains unclear if FC in early‐onset AD (EOAD) would show a similar pattern than late onset AD.
Method
We studied 48 EOAD patients (mean age=57.40±5.53 years) and 31 healthy controls (CTR, mean age=58.22±3.94 years) who underwent resting state functional magnetic resonance imaging (rs‐fMRI) in a 3T MRI scanner. We used group independent component analysis to identify the main resting state networks (RSNs). We studied group‐differences in the spatial extent of these networks, in the amplitude of their temporal oscillations and in the temporal correlation between pairs of networks, using FSLNETS. We also evaluated the discrimination capability of FC patterns by using a support vector machine (SVM) classifier.
Result
We identified 17 RSNs that were further classified into DMN, visual, motor, executive, salience and cerebellum systems. The network spatial maps' vertex‐wise analysis shows regional increases of some executive networks in EOAD (p<0.05, FWE corrected), suggesting increased aberrant local connectivity surrounding the main RSN nodes. In the temporal domain, we find decreases in amplitude in the posterior DMN and the salience network (p<0.05, corrected), and increases in the anterior DMN and the cerebellum networks. With the study of correlations between networks we describe a pattern of altered inter‐network connectivity that involves both increases and decreases of connectivity. Importantly, the entire pattern of network correlations discriminated AD from CTR subjects with an accuracy of 83.5%.
Conclusion
Our results suggest that EOAD is characterized by a complex pattern of FC alterations involving alterations in the amplitude of the main RSNs and in the way that they interconnect. Increase in connectivity in short‐range connections surrounding the main nodes might be a consequence of the decreases of larger connections between nodes. Alterations in the salience network differ from the late onset AD literature. Overall, the entire FC pattern gives a good classification rate suggesting that it might be a good biomarker for EOAD.
PDF
